EP3232282B1 - Dispositif de diagnostic et procede de surveillance du fonctionnement d'une installation technique - Google Patents

Dispositif de diagnostic et procede de surveillance du fonctionnement d'une installation technique Download PDF

Info

Publication number
EP3232282B1
EP3232282B1 EP16164829.0A EP16164829A EP3232282B1 EP 3232282 B1 EP3232282 B1 EP 3232282B1 EP 16164829 A EP16164829 A EP 16164829A EP 3232282 B1 EP3232282 B1 EP 3232282B1
Authority
EP
European Patent Office
Prior art keywords
self
cycle
data set
plant
checked
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
EP16164829.0A
Other languages
German (de)
English (en)
Other versions
EP3232282A1 (fr
Inventor
Thomas Bierweiler
Daniel Labisch
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Siemens AG
Original Assignee
Siemens AG
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Siemens AG filed Critical Siemens AG
Priority to EP16164829.0A priority Critical patent/EP3232282B1/fr
Priority to US15/482,997 priority patent/US10481581B2/en
Priority to CN201710232107.2A priority patent/CN107291063B/zh
Publication of EP3232282A1 publication Critical patent/EP3232282A1/fr
Application granted granted Critical
Publication of EP3232282B1 publication Critical patent/EP3232282B1/fr
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
    • G05B19/4063—Monitoring general control system
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0256—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults injecting test signals and analyzing monitored process response, e.g. injecting the test signal while interrupting the normal operation of the monitored system; superimposing the test signal onto a control signal during normal operation of the monitored system
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • G05B19/0423—Input/output
    • G05B19/0425—Safety, monitoring
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/41805—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by assembly
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/024—Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/32—Circuit design at the digital level
    • G06F30/33—Design verification, e.g. functional simulation or model checking
    • G06F30/3308—Design verification, e.g. functional simulation or model checking using simulation
    • G06F30/3312—Timing analysis
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/24—Pc safety
    • G05B2219/24065—Real time diagnostics

Definitions

  • the invention relates to a diagnostic device for monitoring the operation of a technical system with an automation system according to the preamble of claim 1 and a corresponding diagnostic method according to the preamble of claim 9.
  • Maintenance and servicing of automation equipment can be improved if the correct functioning of units or components is monitored. In case of diminishing functionality it is possible to intervene selectively at the right point of the system with measures for maintenance, repair or troubleshooting.
  • a control device which controls a plant - such as a rolling mill or a sewage treatment plant - automatically, based on the data received from this plant.
  • the data is analyzed to derive a property of the data (feature extraction), and then this property is examined to determine a problem in the operation of the system (problem recognition).
  • this problem is automatically analyzed (cause identification and knowledge management) to derive one or more strategies for the solution (strategy determination); then the plant can be controlled based on this strategy.
  • the analysis can thus be automatically operated as part of a self-organizing mechanism, allowing a higher degree of flexibility and responsiveness of the automatic control.
  • self-organizing maps Kohonen maps or Kohonen networks (after Teuvo Kohonen, English self-organizing map, SOM or self-organizing feature map, SOFM) one designates according to Wikipedia from 04.03.2016 a kind of artificial neural nets.
  • unsupervised learning process they are a powerful tool for data mining. Their functional principle is based on the biological realization that many structures in the brain have a linear or planar topology.
  • predetermined self-organizing map is the later Operating performance compared with the learned error-free behavior. This identifies deviant behavior that can then be analyzed for causes and possible errors in the operation of the process.
  • a disadvantage of the known diagnostic methods is that the time behavior of a running on a technical system process, which could possibly also provide helpful information for a diagnosis is not considered.
  • the invention is therefore based on the object to provide a diagnostic device and a diagnostic method for monitoring the operation of a technical system in which information about the timing are included in the monitoring.
  • the diagnostic device has the features stated in the characterizing part of claim 1.
  • a diagnostic method described in claim 10 a computer program for performing the diagnostic method and in claim 11, a corresponding computer program product.
  • the invention has the advantage that the novel diagnosis is characterized by great flexibility and special simplicity.
  • the self-organizing card is taught-in and parameterized from previously executed fault-free sequencers. Thereby temporal fluctuations in the map are depicted. Both time undershoots and exceedances are automatically taken into account. Also, the case that different lengths of execution times of individual steps occur, so both long and short execution times, but not execution times whose duration is between these extremes and still characterize error-free runs, is represented by the self-organizing map. In this way, the diagnostic options can be further improved.
  • the new diagnostic method is almost applicable to all process, production and process equipment, since technical processes are usually controlled by sequencers, which are also referred to as sequencers or sequential control systems.
  • sequencers which are also referred to as sequencers or sequential control systems.
  • the duration of each step may be subject to both production-related and error-related variations. Timing the steps is useful for detecting deviations, as they may already be considered as evidence of errors.
  • each coordinate for the time duration of the execution of a passing through the teaching process step is.
  • the durations of the individual steps of a sequencer are therefore used as input variables. Since the cycle times on different passes can vary, even if no error occurs, the times of several well-executed passes of the sequencers are used as training data for teaching the self-organizing card.
  • the self-organizing map stores typical expiration times for the individual steps during training at each node from.
  • a 8x12 node card may be used at the beginning of the teaching process.
  • the training data can be used to check the card size. If the card is too big, the individual nodes of the card are not hit or only once from the training data. If a card proved to be too large, a slightly smaller card size can be selected in a next teach-in process and the teach-in process restarted.
  • the new type of diagnosis thus advantageously requires little knowledge of the operator about the system to be monitored and is practically universally applicable. If the execution times of individual steps of a run to be tested deviate too much from those at the previously learned self-organizing map, this is an indication of an error in the monitored system. Only the subsequent analysis of the cause of the error may lead to more detailed knowledge required over the process running on the monitored system.
  • the smallest Cartesian distance between the data record of the test to be tested and the node of the self-organizing card is determined to detect a deviation of the time behavior.
  • the node of the card which has the smallest Cartesian distance to the data record of the pass to be checked is determined as the winner node.
  • a deviation from the normal behavior in the passage of the sequence of steps to be tested is then displayed as a diagnostic statement if the distance to the winner node is one exceeds the predetermined threshold.
  • the threshold values can be determined automatically based on the records of error-free runs.
  • the respective winner nodes can be determined with the data records and the respective Cartesian distances between the data records and the associated winner nodes can be determined.
  • the distance to its winning node resulting in each case for a data record can then be calculated, in each case increased by a safety margin of, for example, 5 to 50%, preferably 15%, and predetermined in this way to avoid misdiagnosis.
  • the predetermination of the nodes of the self-organizing card could be carried out in any desired manner, for example by manual input of the execution times by an operator.
  • an easy-to-implement learning method can be used for the predetermination of the self-organizing card, which requires no complicated input from an operator and hardly any knowledge about the operation of the system.
  • a fault-free operation of the system characterizing records are stored and calculated on the basis of these records through the learning process, the n-tuple with the durations for error-free runs for the nodes of the card and stored on this, d. H. stored assigned to the node.
  • the predetermined in this way card can be used directly for the evaluation of a test to be tested. Of course, can be made by an operator but also subsequently corrections to the individual data of the card.
  • the novel diagnosis is applicable even if branching occurs in a step sequence, due to which alternate steps of the step sequence are performed on different passes.
  • step loops with loops due to which steps of the step sequences can be executed several times in one pass, can be monitored.
  • a coordinate of the n-tuple is set up for each execution of a step of the step sequence in one pass, for steps that are in a loop for each new loop pass. If a loop is traversed less frequently in a pass to be checked, then the value "zero" is stored at the coordinates of the loop steps that are no longer traversed.
  • this type of monitoring can also be usefully applied in situations in which the duration of the execution of a step depends on the number of previous loop passes. In practical cases, the subsequent steps can also be influenced by the number of loop passes.
  • This behavior is therefore also monitored by means of self-organizing maps. From the training data, that is, the records of error-free passes, which are applied when learning the self-organizing map, also the maximum number of loop passes occurring in error-free passes can be determined. If this maximum number is exceeded during the subsequent monitoring of the system, this also indicates a possible fault in the system. On the other hand, if the maximum number of passes in the monitoring is not reached, the values assigned to the non-executed steps are set to "zero" for the duration of execution of the respective step.
  • the diagnostic device can be advantageously designed in an automation environment as a software function block, which can be interconnected in a graphical user interface of an engineering system with function blocks of automation programs and for operating the diagnostic device, for example in an automation device.
  • a so-called faceplate for realizing a man-machine interface on an operating and monitoring device of the automation system then detected deviations from execution times of individual steps that indicate a fault in the system, brought to display.
  • an operator may, if desired, make changes to the self-organizing map or to the thresholds associated with the individual nodes, as a kind of deviation sensitivity.
  • the new diagnostic device for monitoring the operation of a technical system in particular the data memory and the evaluation device, can be implemented in a software environment for cloud-based system monitoring.
  • a software environment represents, for example, the data-based remote service "Control Performance Analytics” from Siemens AG.
  • Data from customer systems are collected with the help of software agents, aggregated, and sent to a Siemens Service Operation Center, in which they are stored on a remote service computer. There they are semi-automatically evaluated with the help of various "Data Analytics" software applications. If required, specially trained experts can work very efficiently on this database for the remote service.
  • the results of the data analysis can be displayed on a monitor of the remote service computer and / or provided on a Sharepoint so that they can be viewed by the end user, ie the operator of the technical installation, for example in a browser.
  • the diagnostic method is thus preferably implemented in software or in a combination of software / hardware, so that the invention also relates to a computer program comprising computer executable program code instructions for implementing the diagnostic method.
  • the invention also relates to a computer program product, in particular a data carrier or a storage medium, with a computer program executable by a computer.
  • a computer program can, as described above, be held in or loaded into a memory of an automation device, so that the operation of the automation device automatically monitors the operation of the technical system, or the computer program can be used for cloud-based monitoring of a technical Plant held in a memory of a remote service computer or be loadable in this.
  • FIG. 1 shows in a simplified schematic representation as an example of a process plant 1, in which a process 2 is controlled by means of an automation system 3.
  • the automation system 3 includes a planning and engineering tool 4, an operating and monitoring device 5 and a plurality of automation devices 6, 7, 8, which are connected to each other via a bus system 9 for data communication.
  • the automation devices 6, 7, 8 control the technical process 2 in accordance with automation programs, of which by way of example in FIG. 1 an automation program 10 is located.
  • the automation program 10 For example, usually consists of several function blocks, which can interact with other distributed in the automation system 3 function blocks.
  • To control the process 2 a variety of field devices 11, 12, 13, 14 are used for process instrumentation.
  • Transmitters are used to record process variables, such as temperature, pressure, flow rate, level, density or gas concentration of a medium.
  • the process sequence can be influenced in accordance with detected process variables, for example, according to the specifications of the automation program 10.
  • actuators may be mentioned a control valve, a heater or a pump.
  • a plurality of data sets which are characteristic of the operation of the system, detected and stored in a data memory 15.
  • an evaluation device 16 the data sets containing execution times of individual steps of step sequences are evaluated in order to determine a diagnosis statement and to indicate to an operator that possibly suitable measures for error handling can be made.
  • sequencers which can also be referred to as sequencers.
  • a sequencer represents a sequence of processing or production steps, for example, stored in an automation program.
  • the duration of each step may be subject to both production-related and error-related variations.
  • the time monitoring of the steps is helpful for detecting deviations and error cases.
  • a sequence of steps described below as an example starts according to FIG. 2 with a step 20 labeled with the word "START”. Steps which are of no significance to the understanding of the present invention have been described in FIG. 2 not provided with a label.
  • a step 21 which bears the label "reactor filling”
  • a reactor is filled, the contents of which then a stirrer is mixed.
  • the reactor is heated according to a step 22, which is provided with the label "heating”. Since different quantities can occur in the reactor, the stirrer power is chosen differently depending on the level.
  • the sequencer therefore has a branch 23 on two alternative paths.
  • a condition 28 with the inscription "T>T_setpoint” is checked and only when it has been performed has it been transferred to the subsequent step 29 with the inscription "stirrer & heater off”.
  • the query 30 thus carries the label "is off”.
  • a step 31 labeled “Transfer to tank” follows, in which the product is transferred to the downstream tank. Steps 21 to 31 are repeated until the desired amount of product is in the tank.
  • the fill level of the tank is smaller than the desired fill level, then the loop is run through again. If, on the other hand, the level of the tank exceeds this limit according to a condition 33 labeled "L_Tank>L_setpoint”, the loop ends and a last step 34 is entered with the label "END” and the sequence is ended.
  • a problem occurring in real operation is, for example, the fouling, ie deposits on inner walls, a heat exchanger used for heating.
  • a stronger fouling manifests itself in a poorer heat transfer and thus an extension of the duration of execution of the step 22, which represents the heating process.
  • the reactor level in the various passes of the loop described above may differ, the duration of the heating phase between each loop iterations varies greatly anyway. A mere monitoring of the duration of the execution of step 22 and comparison with a fixed limit would therefore be less suitable and could only lead to a diagnostic statement of low significance.
  • different threshold values are advantageously calculated automatically for each loop pass, by the evaluation of which a considerably more reliable diagnostic statement can be obtained.
  • the monitoring of the time periods required to execute individual steps will be generically solved based on a self-organizing map.
  • the time periods of the individual steps are used for runs of a sequencer.
  • the times of several well-traveled passes of the sequencers are used as training data.
  • a self-organizing map is obtained which has n-tuple records at each node, with each coordinate of the n-tuple pending execution of a step following an error-free pass.
  • a 8x12-node map can be used to start the learning process.
  • the training data can be used to check the card size. If the map is too big, some nodes of the map will not be hit or only once from the training data. If the map is too big, a slightly smaller map size will be chosen for the further learning process and this map will be taught again based on the training data.
  • threshold values are used to detect a deviation from the normal behavior in the case of a test Passing the step sequence can be used automatically derived from an evaluation of records for error-free runs.
  • the respective winner nodes are determined with the data sets and the maximum Cartesian distances to these are determined.
  • the maximum distance is then increased by a safety surcharge, which may be, for example, between 5 and 50%, preferably 15%. If such a threshold value is exceeded in the subsequent operation of the installation, the diagnosis is obtained that there is a deviation of the record for a test run from the learned self-organizing card, which possibly indicates an error in the system.
  • Lying branches such as those in FIG. 2 branching 23, in step sequences, the steps not executed due to the branch in the record of a pass to be examined are also taken into account by simply assigning the non-executed steps the value "zero" for the duration of their execution.
  • This has the advantage that when a system is monitored by means of a self-organizing map, it is also possible to meaningfully monitor applications in which the time periods of individual steps that are in loops depend on the number of loop passes already made. Furthermore, this approach can handle the case in which the time periods of execution of steps subsequent to the loop are influenced by the number of previous loop passes. Even such behavior can now be taken into account by using a self-organizing map.
  • the maximum number of passes of a loop is determined from the training data, that is to say the records of previously recorded and stored error-free passes which are used to learn the self-organizing map. If a step is executed several times because of a loop, then the times of execution of the step are learned for each pass.
  • the durations for non-traversed steps of the n-tuple of the self-organizing Card up to the learned maximum number are set to the value "zero" analogously to the procedure for branches.
  • the value "zero" is characterized by particularly high plausibility for the user of the diagnosis.
  • runs of sequencers to be checked for its monitoring are evaluated on the basis of the previously trained self-organizing card.
  • the periods of execution of the individual steps are recorded, stored in a data memory and evaluated by means of an evaluation device.
  • That node of the self-organizing map is determined, which has the smallest Cartesian distance to the data set of each pass to be tested. The distance is compared with a predetermined threshold associated with the respective node. If the threshold value is exceeded, there is a deviation from the normal behavior of the system operation, the cause of which may be a system error. For example, on an operating and monitoring device (5 in FIG. 1 ) this is displayed as a diagnostic statement so that an operator can initiate further diagnostics or take appropriate maintenance actions.
  • FIG. 3 shows an example of a representation in which an operator results in monitoring the operation of a technical system can be presented. Successively, nine passes of a step sequence were checked. The number of each run tested is plotted on the X axis, labeled "#Cycle". The ordinate, labeled "Step”, carries the number of the respective step of a step sequence with 36 steps for every fifth step. A point drawn in the diagram indicates that the determined time duration of the execution of the respective step has no impermissible deviations from a faultless pass. A cross, marked as "x”, represents a longer step duration than expected for a flawless pass, a circle for a shorter one.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Evolutionary Computation (AREA)
  • Computer Hardware Design (AREA)
  • Manufacturing & Machinery (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Theoretical Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Human Computer Interaction (AREA)
  • Geometry (AREA)
  • Testing And Monitoring For Control Systems (AREA)

Claims (11)

  1. Dispositif de diagnostic pour contrôler le fonctionnement d'une installation (1) technique ayant un système (3) d'automatisation, le dispositif de diagnostic comprenant une mémoire (15) de données, dans laquelle au moins un jeu de données caractérisant le fonctionnement de l'installation peut être mémorisé, et un dispositif (16) d'exploitation par lequel, à l'aide du jeu de données et d'une carte définie à l'avance dite auto-organisatrice, un diagnostic sur le fonctionnement de l'installation (1) peut être déterminé et/ou affiché, caractérisé,
    en ce que le dispositif (16) d'exploitation est constitué pour, lorsque l'installation fonctionne en ayant des chaînes de stades se déroulant de manière répétée, déterminer les durées de la réalisation de chaque stade d'un déroulement à contrôler d'une chaîne de stades et les mémoriser sous la forme d'une coordonnée du jeu de données, le jeu de données étant réalisé sous la forme d'un n-tuple ayant un nombre n défini à l'avance de coordonnées,
    en ce que des n-tuples, correspondant aux noeuds de la carte auto-organisatrice, sont mémorisés avec des durées définies à l'avance pour des déroulements sans erreur de la chaîne de stades et
    en ce que le dispositif (16) d'exploitation est constitué, en outre, pour, par exploitation du jeu de données à l'aide de la carte auto-organisatrice, détecter et afficher un écart du comportement dans le temps, lors du déroulement à contrôler de la chaîne de stades, au comportement dans le temps pour des déroulements sans erreur.
  2. Dispositif de diagnostic suivant la revendication 1, caractérisé en ce que le dispositif (16) d'exploitation est constitué pour déterminer, pour la détection, un écart du comportement dans le temps de la distance cartésienne la plus petite entre le jeu de données du déroulement à contrôler et les noeuds de la carte auto-organisatrice.
  3. Dispositif de diagnostic suivant la revendication 2, caractérisé en ce que le dispositif (16) d'exploitation est constitué pour afficher, comme diagnostic, un écart au comportement normal lors du déroulement à contrôler de la chaîne de stades, si la distance dépasse une valeur de seuil définie à l'avance.
  4. Dispositif de diagnostic suivant l'une des revendications précédentes, caractérisé en ce que le dispositif (16) d'exploitation est constitué pour mémoriser, afin de définir à l'avance la carte auto-organisatrice avant un déroulement à contrôler, dans la mémoire (15) de données, plusieurs jeux de données caractérisant un fonctionnement sans erreur de l'installation et, à l'aide de ces jeux de données, pour calculer, pour les noeuds, par un procédé d'apprentissage, les n-tuples ayant les durées de la réalisation des stades pour des déroulements sans erreur et les mémoriser sur les noeuds de la carte auto-organisatrice.
  5. Dispositif de diagnostic suivant la revendication 4, caractérisé en ce que le dispositif (16) d'exploitation est constitué, en outre, pour mémoriser, avant un déroulement à contrôler, dans la mémoire (15) de données, d'autres jeux de données caractérisant un fonctionnement sans erreur de l'installation, pour déterminer, pour les jeux de données, respectivement un noeud gagnant, pour calculer les distances maximum respectives des jeux de données aux noeuds gagnants qui leur sont associés et pour mémoriser celles-ci, respectivement augmentées d'un supplément pour empêcher des diagnostics défectueux, comme valeurs de seuil déterminées à l'avance, associées respectivement aux noeuds gagnants.
  6. Dispositif de diagnostic suivant l'une des revendications précédentes, caractérisé en ce que le dispositif (16) d'exploitation est constitué pour, lors d'une ramification (23) dans une chaîne de stades, sur la base de laquelle des stades alternatifs de la chaîne de stades peuvent être réalisés lors d'un déroulement, fixer la valeur "zéro" pour des stades non réalisés dans un déroulement à contrôler et à la mémoriser pour la coordonnée du jeu de données, qui est prévue pour le stade non réalisé.
  7. Dispositif de diagnostic suivant l'une des revendications précédentes, caractérisé en ce que le dispositif (16) d'exploitation est constitué pour, en présence d'une boucle dans une chaîne de stades, sur la base de laquelle des stades de la chaîne de stades peuvent être réalisés plusieurs fois lors d'un déroulement, établir, lors de l'apprentissage de la carte auto-organisatrice, à l'aide de déroulement sans erreur pour chaque réalisation des stades de la chaîne de stades dans un déroulement, une coordonnée du n-tuple et fixer, comme durée, la valeur "zéro" pour des stades de la boucle, qui ne sont pas réalisés dans un déroulement à contrôler de la chaîne de stades, et la mémoriser pour la coordonnée du jeu de données, qui est associée au stade de boucle non réalisé.
  8. Dispositif de diagnostic suivant l'une des revendications précédentes, caractérisé en ce qu'au moins la mémoire (15) de données et le dispositif (16) d'exploitation sont mis en oeuvre par logiciel sur un ordinateur de service à distance pour le télédiagnostic de l'installation (1).
  9. Procédé de diagnostic pour contrôle le fonctionnement d'une installation (1) technique, comprenant les stades suivants :
    - mémorisation d'au moins un jeu de données caractérisant le fonctionnement de l'installation (1) dans une mémoire (15) de données,
    - détermination d'un diagnostic sur le fonctionnement de l'installation à l'aide du jeu de données et d'une carte dite auto-organisatrice définie à l'avance,
    caractérisé par les autres stades, qui sont réalisés dans un fonctionnement de l'installation ayant des chaînes de stades se déroulant de manière répétée :
    - détermination de la durée de la réalisation de chaque stade d'un déroulement à contrôle d'une chaîne de stades,
    - mémorisation des durées déterminées auparavant, comme respectivement une coordonnée du jeu de données, le jeu de données étant réalisé en n-tuple ayant un nombre n défini à l'avance de coordonnées,
    - détection et affichage d'écart du comportement dans le temps lors du déroulement à contrôler de déroulement sans erreur par exploitation du jeu de données à l'aide de la carte auto-organisatrice, dans lequel, sur les noeuds de la carte auto-organisatrice, des n-tuples, ayant les durées définies à l'avance pour des déroulements sans erreur de la chaîne de stades, sont mémorisés.
  10. Programme d'ordinateur ayant des instructions de code de programme pouvant être réalisées par un ordinateur pour la mise en oeuvre du procédé suivant la revendication 9, lorsque le programme d'ordinateur est réalisé sur un ordinateur.
  11. Produit de programme d'ordinateur, notamment support de données ou support de mémoire ayant un programme d'ordinateur pouvant être réalisé par un ordinateur suivant la revendication 10.
EP16164829.0A 2016-04-12 2016-04-12 Dispositif de diagnostic et procede de surveillance du fonctionnement d'une installation technique Active EP3232282B1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
EP16164829.0A EP3232282B1 (fr) 2016-04-12 2016-04-12 Dispositif de diagnostic et procede de surveillance du fonctionnement d'une installation technique
US15/482,997 US10481581B2 (en) 2016-04-12 2017-04-10 Diagnosis facility and diagnostic method for monitoring performance of a technical plant
CN201710232107.2A CN107291063B (zh) 2016-04-12 2017-04-11 用于监控技术设施的运行的诊断装置和诊断方法

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
EP16164829.0A EP3232282B1 (fr) 2016-04-12 2016-04-12 Dispositif de diagnostic et procede de surveillance du fonctionnement d'une installation technique

Publications (2)

Publication Number Publication Date
EP3232282A1 EP3232282A1 (fr) 2017-10-18
EP3232282B1 true EP3232282B1 (fr) 2018-09-12

Family

ID=55759471

Family Applications (1)

Application Number Title Priority Date Filing Date
EP16164829.0A Active EP3232282B1 (fr) 2016-04-12 2016-04-12 Dispositif de diagnostic et procede de surveillance du fonctionnement d'une installation technique

Country Status (3)

Country Link
US (1) US10481581B2 (fr)
EP (1) EP3232282B1 (fr)
CN (1) CN107291063B (fr)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3324254A1 (fr) * 2016-11-17 2018-05-23 Siemens Aktiengesellschaft Dispositif et procédé de détermination des paramètres d'un dispositif de réglage
EP3495900A1 (fr) 2017-12-11 2019-06-12 Siemens Aktiengesellschaft Optimisation de processus sur la base des cartes auto-organisatrices
CN108960423A (zh) * 2018-06-22 2018-12-07 青岛鹏海软件有限公司 基于机器学习的电机监测系统
EP3591482B1 (fr) * 2018-07-03 2024-06-12 Siemens Aktiengesellschaft Surveillance d'une installation technique
JP2020173168A (ja) * 2019-04-10 2020-10-22 大日防蝕化工株式会社 ライニングの非破壊劣化検査方法
KR102342476B1 (ko) 2019-10-25 2021-12-24 한국과학기술연구원 시설의 센싱 데이터를 이미지화하여 시설의 상태를 판단하는 시스템 및 방법
CN115219912A (zh) * 2022-04-24 2022-10-21 山东大学 一种储能电池早期故障诊断与安全超前预警方法及系统
CN116882946B (zh) * 2023-09-06 2024-01-19 南京南自华盾数字技术有限公司 一种基于发电企业数据的智能化管理系统及方法

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0351833B1 (fr) 1988-07-20 1996-06-12 Mitsubishi Jukogyo Kabushiki Kaisha Système de diagnostic de défauts pour usines
JPH03259302A (ja) * 1990-03-09 1991-11-19 Hitachi Ltd 情報処理システム
DE10244131B4 (de) 2002-09-23 2006-11-30 Siemens Ag Verfahren zur Unterstützung einer Identifizierung einer defekten Funktionseinheit in einer technischen Anlage
JP4032045B2 (ja) * 2004-08-13 2008-01-16 新キャタピラー三菱株式会社 データ処理方法及びデータ処理装置、並びに診断方法及び診断装置
JP2008190454A (ja) * 2007-02-06 2008-08-21 Toyota Motor Corp 空燃比センサの異常診断装置及び異常診断方法
US20120310850A1 (en) * 2010-07-16 2012-12-06 Sap Ag Method and System for Evaluating Events
EP2472440B1 (fr) 2011-01-04 2014-06-25 Siemens Aktiengesellschaft Procédé et système pour le diagnostic du statut d'une installation
CN102419593B (zh) 2011-10-08 2013-07-10 济中节能技术（苏州）有限公司 基于数据挖掘的传感器故障诊断方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
None *

Also Published As

Publication number Publication date
CN107291063A (zh) 2017-10-24
US10481581B2 (en) 2019-11-19
EP3232282A1 (fr) 2017-10-18
CN107291063B (zh) 2019-09-13
US20170308056A1 (en) 2017-10-26

Similar Documents

Publication Publication Date Title
EP3232282B1 (fr) Dispositif de diagnostic et procede de surveillance du fonctionnement d'une installation technique
EP3279756B1 (fr) Dispositif de diagnostic et procédé de surveillance du fonctionnement d'une installation technique
EP0789861B1 (fr) Procede d'analyse des donnees d'operations d'une installation technique
EP3591482B1 (fr) Surveillance d'une installation technique
EP3282399B1 (fr) Procede de reconnaissance ameliore d'anomalies de processus d'une installation technique et systeme de diagnostic correspondant
DE19743600B4 (de) Verfahren zur Überwachung eines zyklischen Produktionsprozesses
WO2001055805A1 (fr) Systeme et procede pour determiner l'efficacite d'unites de production, des evenements d'erreurs et la cause desdites erreurs
EP3077878B1 (fr) Procédé implémenté par ordinateur et système de surveillance automatique et de détermination de l'état de l'intégralité des étapes de processus dans une unité de traitement
EP3876060B1 (fr) Procédé et unité de calcul destinés à l'analyse des causes d'un état anormal d'une machine
EP0789864B1 (fr) Systeme de controle pour installation industrielle
EP2568348A1 (fr) Aide au diagnostic d'erreurs d'une installation industrielle
EP3876062B1 (fr) Procédé et unité de calcul destinés à la surveillance de l'état d'une machine
EP4060433A1 (fr) Procédé et système de prévision du fonctionnement d'une installation technique
WO2009068228A1 (fr) Système et procédé d'acquisition d'informations combiné pour applications de scada et de simulation ou d'estimation de réseaux
DE102019215016A1 (de) Messanordnung, Verfahren zum Einrichten einer Messanordnung und Verfahren zum Betreiben einer Messanordnung
EP4193227A1 (fr) Dispositif et procédé de détection d'anomalies dans une installation industrielle pour l'exécution d'un processus de production
EP1958101B1 (fr) Systeme et procede de verification automatique de resultats de conception
DE102019208922A1 (de) Verfahren und Vorrichtung zum Kontrollieren eines Produktionsprozesses
EP4060441A1 (fr) Procédé et système de détection des anomalies dans le fonctionnement d'une installation technique
EP1507181B1 (fr) Procédé et dispositif de traitement de données à niveaux multiples, en particulier pour diagnostiques, dans une installation technique
WO2021191190A1 (fr) Procédé et système de diagnostic de messages
EP3748449A1 (fr) Analyse des causes des messages d'un système technique
EP1883874B1 (fr) Procede pour surveiller une installation industrielle automatisee
EP2402832A1 (fr) Procédé et système d'affichage pour le calibrage d'affichages normalisés de grandeurs de processus
EP4063980A1 (fr) Analyse de causes d'une anomalie en fonction de symptômes simulés

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION HAS BEEN PUBLISHED

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

AX Request for extension of the european patent

Extension state: BA ME

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20180205

RBV Designated contracting states (corrected)

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

GRAP Despatch of communication of intention to grant a patent

Free format text: ORIGINAL CODE: EPIDOSNIGR1

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: GRANT OF PATENT IS INTENDED

RIC1 Information provided on ipc code assigned before grant

Ipc: G05B 19/418 20060101ALI20180515BHEP

Ipc: G05B 23/02 20060101AFI20180515BHEP

Ipc: G05B 19/4063 20060101ALI20180515BHEP

Ipc: G05B 19/425 20060101ALI20180515BHEP

Ipc: G06F 17/50 20060101ALI20180515BHEP

INTG Intention to grant announced

Effective date: 20180607

GRAS Grant fee paid

Free format text: ORIGINAL CODE: EPIDOSNIGR3

GRAA (expected) grant

Free format text: ORIGINAL CODE: 0009210

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE PATENT HAS BEEN GRANTED

AK Designated contracting states

Kind code of ref document: B1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

REG Reference to a national code

Ref country code: GB

Ref legal event code: FG4D

Free format text: NOT ENGLISH

REG Reference to a national code

Ref country code: CH

Ref legal event code: EP

REG Reference to a national code

Ref country code: IE

Ref legal event code: FG4D

Free format text: LANGUAGE OF EP DOCUMENT: GERMAN

REG Reference to a national code

Ref country code: DE

Ref legal event code: R096

Ref document number: 502016001898

Country of ref document: DE

REG Reference to a national code

Ref country code: AT

Ref legal event code: REF

Ref document number: 1041346

Country of ref document: AT

Kind code of ref document: T

Effective date: 20181015

REG Reference to a national code

Ref country code: NL

Ref legal event code: MP

Effective date: 20180912

REG Reference to a national code

Ref country code: LT

Ref legal event code: MG4D

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: FI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: RS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: NO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20181212

Ref country code: BG

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20181212

Ref country code: SE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: GR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20181213

Ref country code: LT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: AL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: LV

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: HR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: ES

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: NL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: PL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: IS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20190112

Ref country code: RO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: CZ

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: IT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: EE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SM

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: SK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

Ref country code: PT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20190112

REG Reference to a national code

Ref country code: DE

Ref legal event code: R097

Ref document number: 502016001898

Country of ref document: DE

PLBE No opposition filed within time limit

Free format text: ORIGINAL CODE: 0009261

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: DK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

26N No opposition filed

Effective date: 20190613

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

REG Reference to a national code

Ref country code: CH

Ref legal event code: PL

REG Reference to a national code

Ref country code: BE

Ref legal event code: MM

Effective date: 20190430

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: LU

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190412

Ref country code: MC

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: LI

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190430

Ref country code: CH

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190430

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: BE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190430

Ref country code: FR

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190430

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: TR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190412

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: CY

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: HU

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT; INVALID AB INITIO

Effective date: 20160412

Ref country code: MT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

REG Reference to a national code

Ref country code: AT

Ref legal event code: MM01

Ref document number: 1041346

Country of ref document: AT

Kind code of ref document: T

Effective date: 20210412

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: MK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180912

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: AT

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210412

PGFP Annual fee paid to national office [announced via postgrant information from national office to epo]

Ref country code: DE

Payment date: 20220620

Year of fee payment: 8

PGFP Annual fee paid to national office [announced via postgrant information from national office to epo]

Ref country code: GB

Payment date: 20240507

Year of fee payment: 9